Context-Dependent Data Envelopment Analysis with Interval Data
نویسندگان
چکیده
منابع مشابه
Context-Dependent Data Envelopment Analysis-Measuring Attractiveness and Progress with Interval Data
Data envelopment analysis (DEA) is a method for recognizing the efficient frontier of decision making units (DMUs).This paper presents a Context-dependent DEA which uses the interval inputs and outputs. Context-dependent approach with interval inputs and outputs can consider a set of DMUs against the special context. Each context shows an efficient frontier including DMUs in particular l...
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Data envelopment analysis (DEA) is a non-parametric method for evaluating the relative efficiency of decision making units (DMUs) on the basis of multiple inputs and outputs. The context-dependent DEA is introduced to measure the relative attractiveness of a particular DMU when compared to others. In real-world situation, because of incomplete or non-obtainable information, the data (Input and ...
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System designs, optimizing resource allocation to organization units, is still being considered as a complicated problem especially when there are multiple inputs and outputs related to a unit. The algorithm presented here will divide the frontiers obtained with DEA. In this way, we investigate a new approach for resource allocation.
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system designs, optimizing resource allocation to organization units, is still being considered as a complicated problem especially when there are multiple inputs and outputs related to a unit. the algorithm presented here will divide the frontiers obtained with dea. in this way, we investigate a new approach for resource allocation.
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In the process of production, some of the inputs are fixed and cannot easily be changed, such as work hours of workers and hours of administrative or work, these types of inputs are fixed and others are variables. In this paper, by considering some inputs or outputs which are limited, their amounts must be integrated; this concept for integer data is extended. We show the importance of subject ...
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ژورنال
عنوان ژورنال: American Journal of Computational Mathematics
سال: 2011
ISSN: 2161-1203,2161-1211
DOI: 10.4236/ajcm.2011.14031